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The American Journal of Managed Care October 2006
Implementation of Evidence-based Alcohol Screening in the Veterans Health Administration
Katherine A. Bradley, MD, MPH; Emily C. Williams, MPH; Carol E. Achtmeyer, MN; Bryan Volpp, MD; Bonny J. Collins, PA-C, MPA; and Daniel R. Kivlahan, PhD
Low-density Lipoprotein Cholesterol Goal Attainment Among High-risk Patients: Does a Combined Intervention Targeting Patients and Providers Work?
Nelia M. Afonso, MD; George Nassif, MD; Anil N. F. Aranha, PhD; Bonnie DeLor, PharmD; and Lavoisier J. Cardozo, MD
Outpatient Medication Use and Health Outcomes in Post-Acute Coronary Syndrome Patients
Zhou Yang, PhD, MPH; Ade Olomu, MD; William Corser, PhD; David R. Rovner, MD; and Margaret Holmes-Rovner, PhD
Low-density Lipoprotein Cholesterol Goal Attainment Among High-risk Patients: Does a Combined Intervention Targeting Patients and Providers Work?
Nelia M. Afonso, MD; George Nassif, MD; Anil N. F. Aranha, PhD; Bonnie DeLor, PharmD; and Lavoisier J. Cardozo, MD
Association of Income and Prescription Drug Coverage With Generic Medication Use Among Older Adults With Hypertension
Alex D. Federman, MD, MPH; Ethan A. Halm, MD, MPH; Carolyn Zhu, PhD; Tsivia Hochman, MA; and Albert L. Siu, MD, MSPH
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Outpatient Medication Use and Health Outcomes in Post-Acute Coronary Syndrome Patients
Zhou Yang, PhD, MPH; Ade Olomu, MD; William Corser, PhD; David R. Rovner, MD; and Margaret Holmes-Rovner, PhD
Association of Income and Prescription Drug Coverage With Generic Medication Use Among Older Adults With Hypertension
Alex D. Federman, MD, MPH; Ethan A. Halm, MD, MPH; Carolyn Zhu, PhD; Tsivia Hochman, MA; and Albert L. Siu, MD, MSPH
Increasing Primary Care Physician Productivity: A Case Study
Steven Lewandowski, BSS; Patrick J. O'Connor, MD, MPH; Leif I. Solberg, MD; Thomas Lais, BS; Mary Hroscikoski, MD; and JoAnn M. Sperl-Hillen, MD
Increasing Primary Care Physician Productivity: A Case Study
Steven Lewandowski, BSS; Patrick J. O'Connor, MD, MPH; Leif I. Solberg, MD; Thomas Lais, BS; Mary Hroscikoski, MD; and JoAnn M. Sperl-Hillen, MD

Outpatient Medication Use and Health Outcomes in Post-Acute Coronary Syndrome Patients

Zhou Yang, PhD, MPH; Ade Olomu, MD; William Corser, PhD; David R. Rovner, MD; and Margaret Holmes-Rovner, PhD

Objective: To investigate the pattern of postdischarge evidencebased outpatient medication use and its impact on subsequent hospital readmissions in post-acute coronary syndrome (ACS) patients.

Study Design: Prospective observational study.

Methods: A telephone survey was conducted to collect information from discharge to 8 months after discharge for 433 patients hospitalized with a primary diagnosis of ACS in 5 mid-Michigan hospitals. The survey data were then merged with chart review data from the initial hospitalization. We first conducted a longitudinal descriptive analysis of the utilization patterns of patient self-reported medication use from discharge to the 8-month survey. Then, multivariable logit analysis was used to estimate the effect of post-ACS medication use on self-reported hospital readmission at 3 months and 8 months after discharge. Propensity score matching was used to counter the possible bias induced by self-selection of outpatient medication use.

Results: The pattern of outpatient medication use was dynamic. Most changes to medication regimens occurred within 3 months after discharge, with fewer changes in the subsequent 5 months. Taking a ß-blocker, angiotensin-converting enzyme inhibitor, or angiotension receptor blocker significantly reduced the probability of hospital readmission 3 months after discharge. Propensity score matching produced similar statistically significant results. Rehospitalization within 3 months after discharge was a strong predictor of later hospital readmission up to 8 months.

Conclusion: Timely and appropriate medication adjustment in outpatient settings appears to be critically important to reduce hospital readmission among ACS patients.

(Am J Manag Care. 2006;12:581-587)


Cardiovascular disease is one of the major threats to people's health in the United States. Each year, acute coronary syndrome (ACS) episodes result in more than 1.4 million hospital admissions and 20% of deaths from all causes.1 Randomized clinical trials have established a set of medications widely recognized to improve survival and quality of life of ACS patients. The national practice guidelines from the American College of Cardiology (ACC) and American Heart Association (AHA) promote continuous use of these evidence-based medications after ACS to prevent death and secondary complications.2 These medications include angiotensinconverting enzyme inhibitors (ACEIs) (or angiotension receptor blockers [ARBs] as appropriate), ß-blockers, lipid-lowering medications, and aspirin. Despite the general consensus regarding their clinical efficacy, previous research has consistently shown underprescription and inadequate utilization of these medications in outpatient clinical settings.3-8 These problems have been attributed to inconsistent acceptance of practice guidelines as well as problems with coordination among inpatient physicians, outpatient physicians, pharmacists, patients themselves, and insurance companies.

Hospital discharge offers a major opportunity for quality improvement intervention, because it is the linkage point between inpatient care and outpatient care. ACC and AHA have particularly targeted discharge for application of practice guidelines to prescribe evidence-based medicines. Existing research is encouraging, suggesting that both filling prescriptions and adherence to cardiac medications are improved by complete hospital discharge recommendations.3,9,10 However, outpatient care for ACS patients is more complicated than adherence versus nonadherence to discharge medications because of the complex healthcare environment and long-term course of follow-up. Patients may add, switch, or drop their discharge medications due to transfer of care to another physician, change in health condition, medication side effects, or changes in insurance coverage. Compared with the body of existing research that focuses on effectiveness of quality improvement interventions in hospitals,3,11,12 little health services research has focused on outpatient care after an acute episode of cardiovascular disease to investigate patterns of long-term medication use and its impact on health outcomes in patients with ACS or acute myocardial infarction (AMI).

The purposes of this investigation were to (1) analyze patterns of medication use from discharge to 8 months in patients with an initial ACS diagnosis in any of the 5 mid-Michigan hospitals participating in this study and (2) use multivariable regression analysis to investigate how the use of these medications affected subsequent rates of hospital readmission.

METHODS

Data

We evaluated postdischarge cardiovascular health behaviors and medication use in patients hospitalized for ACS in 5 mid-Michigan hospitals from 2002 to 2003. Inclusion criteria were aged 21 years or older, a working diagnosis of ACS or AMI in the medical record, and a documented serum troponin I level equal to or greater than the upper limits of normal for that hospital during hospitalization. Exclusion criteria included inability to speak English or complete study interviews or discharge to a nonhome setting.

The study data came from 2 sources: medical record review and postdischarge patient telephone survey. Demographic features, clinical examination results, inhospital procedure, and most importantly, discharge medication data were collected from review of hospital medical records. All medical record data including medication use were collected by trained nurse chart abstractors supervised by the study community project manager. Each chart abstractor used a standard data collection sheet and made periodic reference to a chart abstraction manual concerning specific data fields and parameters. Ongoing chart abstractor team meetings were conducted to review and refine chart audit processes, and maintain reliability of data entry.

Posthospital telephone surveys lasting approximately 30 to 40 minutes were conducted by trained survey researchers from the Institute for Public Policy and Social Research of Michigan State University at 3 time points: after discharge from the index hospital (mean of 14.1 days after discharge [SD = 9.6 days]), 3 months after discharge, and 8 months after discharge. In the telephone interview, patients were asked by interviewers to collect the bottles of each of their currently used prescription medications and read off the names as well as the dosage of the medications. Interviewers also asked about changes in medication use, including adding, dropping, or switching medications since the prior interview. The hospital readmission also was reported, but differentiated from emergency department visits in the survey. Patients were specifically asked to tell interviewers whether they had ever visited a hospital emergency department and/or been admitted to a hospital for at least 1 night at 3 months and 8 months after their initial hospital discharge. However, the survey did not determine whether an emergency department visit led to a hospital readmission, or the specific reason for hospital readmission. Reasons for readmission, therefore, include cardiac and noncardiac diseases. Participation in any hospital-or home-based cardiac rehabilitation program was also assessed during the telephone survey, and patients were systematically asked about rehabilitation participation since the prior interview. Information related to health behaviors (eg, smoking, drinking) was also collected.

Sample

A total of 719 patients were enrolled in the initial study, of whom 527 (73%) completed a postdischarge baseline interview. Among those who completed a baseline interview, 433 (82%) completed a 3-month interview, and 381 (88%) of these patients also completed an 8-month interview. Based on the Michigan vital statistics record, the mortality rate was very low (n = 10). No demographic features or hospital care variables differed between the survivors who dropped out of the survey and those who remained in the study. However, smoking, depression, and having better functional status were predictive of attrition, after adjusting for mortality. Because the focus of this study was the impact of evidencebased medication use on health outcomes for post-ACS patients, we included only the 433 patients who completed at least both a baseline interview and a 3-month follow-up interview.

Measurements

Study measures came from the chart abstract and phone survey. Patients' demographic characteristics and clinical information, including diagnoses, comorbidities, clinical examination results, and discharge medication, were obtained from chart review. Although the baseline survey collected information about medication use shortly after discharge, we used medication prescribed at discharge as the more reliable measurement of medication availability. Outpatient medication use at 3 months or 8 months, hospital readmission, enrollment in rehabilitation services, and health-related behaviors came from the baseline, 3-month, and 8-month surveys.

We categorized the medications into 2 groups for this analysis: (1) cardiac medications, which are the drugs recommended by ACC and AHA to treat cardiovascular disease and its related symptoms, including ACEIs, ARBs, b-blockers, lipid-lowering medications (almost entirely comprised of statin medications), and aspirin and (2) all other medications prescribed for noncardiac-related clinical conditions.

Severity of ACS and general health status measures include ejection fraction, Duke Activity Status Index (DASI), and Charlson Comorbidity Index (CCI).13 As an overall measure of cardiac functioning, ejection fraction was measured during the initial hospitalization, and hence was obtained from the chart review for the entire study sample and dichotomized at an ejection fraction less than or equal to 35%.14,15 The DASI was used to measure patients' functional status. It is a weighted composite score computed from answers to questions about 12 activities of daily living of progressive intensity. DASI scores have been shown to be highly correlated with oxygen uptake on treadmill exercise,16 and has adequate sensitivity to show clinical changes in physical function for both surgical cardiac patients17,18 and nonsurgical cardiac patients.19,20 In addition, this tool has been demonstrated to be significantly correlated with other measures of cardiovascular fitness.21 Scale scores for the DASI range from 0 to 58.2 points, with a higher composite score indicating greater functional capacity. In our study, the 12 DASI daily activities were evaluated at baseline survey for each subject. We then calculated the DASI score based on the survey data.

CCI was used as the measurement of comorbidity.13 Patients' composite CCI score was the weighted sum of the presence of 19 medical conditions documented in their medical record including diabetes, myocardial infarction, peripheral vascular disease, and so forth. The CCI score in this study was calculated by the comorbidities reported in the chart review.

Descriptive Analyses

We first performed a descriptive analysis of patterns of cardiac medication use and instances of postdischarge hospital readmission. The purpose of the descriptive analysis was to examine the dynamic features of postacute care for ACS, particularly changing patterns of outpatient prescription medication use.

Multivariable Regression Analyses

After the descriptive analysis, we performed multivariable logit regression modeling using Stata software (StataCorp, College Station, Tex) to estimate the association between cardiac medication use and hospital readmission at 3 months or 8 months after initial hospitalization for ACS patients. The dependent variables in the model were hospital readmission at 3 months or 8 months after discharge. The major independent variables included whether the patient reported using 1 or more selected cardiac medicationsincluding ACEIs/ARBs, ß-blockers, or both; lipid-lowering medications; or aspirinby the time of the 3-month or 8-month surveys. Other independent variables included patient demographics (age, sex, race, marital status, years of education), socioeconomic status (whether a patient's household income was below the national poverty level), clinical and health status variables (ejection fraction, DASI, CCI), health-related behaviors (smoking, drinking), and participation in either formal or informal cardiac rehabilitation. We set the threshold of significance at P = .1 for the statistical analysis.

Propensity Score Matching

 
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